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16th EDM 2023: Bengaluru, India
- Mingyu Feng, Tanja Käser, Partha P. Talukdar, Rakesh Agrawal, Y. Narahari, Mykola Pechenizkiy:
Proceedings of the 16th International Conference on Educational Data Mining, EDM 2023, Bengaluru, India, July 11-14, 2023. International Educational Data Mining Society 2023
Full Papers
- Janine Langebein, Till Massing, Jens Klenke, Michael Striewe, Michael Goedicke, Christoph Hanck, Natalie Reckmann:
A Data Mining Approach for Detecting Collusion in Unproctored Online Exams. - Philip I. Pavlik Jr., Luke G. Eglington:
Automated Search for Logistic Knowledge Tracing Models. - Yang Shi, Robin Schmucker, Min Chi, Tiffany Barnes, Thomas W. Price:
KC-Finder: Automated Knowledge Component Discovery for Programming Problems. - Preya Shabrina, Behrooz Mostafavi, Sutapa Dey Tithi, Min Chi, Tiffany Barnes:
Learning Problem Decomposition-Recomposition with Data-driven Chunky Parsons Problems within an Intelligent Logic Tutor. - Hamid Karimi, Kaitlin Torphy Knake, Kenneth A. Frank:
An Analysis of Diffusion of Teacher-curated Resources on Pinterest. - Harshita Chopra, Yiwen Lin, Mohammad Amin Samadi, Jacqueline G. Cavazos, Renzhe Yu, Spencer Jaquay, Nia Nixon:
Semantic Topic Chains for Modeling Temporality of Themes in Online Student Discussion Forums. - Muntasir Hoq, Peter Brusilovsky, Bita Akram:
Analysis of an Explainable Student Performance Prediction Model in an Introductory Programming Course. - Mélina Verger, Sébastien Lallé, François Bouchet, Vanda Luengo:
Is Your Model "MADD"? A Novel Metric to Evaluate Algorithmic Fairness for Predictive Student Models. - Afrizal Doewes, Nughthoh Arfawi Kurdhi, Akrati Saxena:
Evaluating Quadratic Weighted Kappa as the Standard Performance Metric for Automated Essay Scoring. - Aaron Haim, Robert Gyurcsan, Chris Baxter, Stacy T. Shaw, Neil T. Heffernan:
How to Open Science: Debugging Reproducibility within the Educational Data Mining Conference. - Lea Cohausz, Andrej Tschalzev, Christian Bartelt, Heiner Stuckenschmidt:
Investigating the Importance of Demographic Features for EDM-Predictions. - Anup Shakya, Vasile Rus, Deepak Venugopal:
Scalable and Equitable Math Problem Solving Strategy Prediction in Big Educational Data. - Boxuan Ma, Gayan Prasad Hettiarachchi, Sora Fukui, Yuji Ando:
Exploring the effectiveness of Vocabulary Proficiency Diagnosis Using Linguistic Concept and Skill Modeling. - Hagit Gabbay, Anat Cohen:
Unfolding Learners' Response to Different Versions of Automated Feedback in a MOOC for Programming - A Sequence Analysis Approach. - Kerstin Wagner, Agathe Merceron, Petra Sauer, Niels Pinkwart:
Can the Paths of Successful Students Help Other Students With Their Course Enrollments? - Antonette Shibani, Ratnavel Rajalakshmi, Faerie Mattins, Srivarshan Selvaraj, Simon Knight:
Visual representation of co-authorship with GPT-3: Studying human-machine interaction for effective writing. - Jauwairia Nasir, Aditi Kothiyal, Haoyu Sheng, Pierre Dillenbourg:
To speak or not to speak, and what to speak, when doing task actions collaboratively. - Husni Almoubayyed, Stephen Fancsali, Steven Ritter:
Generalizing Predictive Models of Reading Ability in Adaptive Mathematics Software.
Short Papers
- Vishal Kiran Kuvar, Lauren E. Flynn, Laura K. Allen, Caitlin Mills:
Partner Keystrokes can Predict Attentional States during Chat-based Conversations. - Amir Zur, Isaac Applebaum, Jocelyn Nardo, Dory DeWeese, Sameer Sundrani, Shima Salehi:
Meta-Learning for Better Learning: Using Meta-Learning Methods to Automatically Label Exam Questions with Detailed Learning Objectives. - Ayaz Karimov, Mirka Saarela, Tommi Kärkkäinen:
Clustering to define interview participants for analyzing student feedback: a case of Legends of Learning. - Wei Chu, Philip I. Pavlik Jr.:
The Predictiveness of PFA is Improved by Incorporating the Learner's Correct Response Time Fluctuation. - Stephen Hutt, Sanchari Das, Ryan Baker:
The Right To Be Forgotten and Educational Data Mining: Challenges and Paths Forward. - Yunsung Kim, Sreechan Sankaranarayanan, Chris Piech, Candace Thille:
Variational Temporal IRT: Fast, Accurate, and Explainable Inference of Dynamic Learner Proficiency. - Md. Akib Zabed Khan, Agoritsa Polyzou:
Session-based Course Recommendation Frameworks using Deep Learning. - Zilin Dai, Andrew A. McReynolds, Jacob Whitehill:
In Search of Negative Moments: Multi-Modal Analysis of Teacher Negativity in Classroom Observation Videos. - Machi Shimmei, Noboru Matsuda:
Can't Inflate Data? Let the Models Unite and Vote: Data-agnostic Method to Avoid Overfit with Small Data. - Morgan P. Lee, Ethan A. Croteau, Ashish Gurung, Anthony F. Botelho, Neil T. Heffernan:
Knowledge Tracing Over Time: A Longitudinal Analysis. - Valdemar Svábenský, Ryan Baker, Andrés Zambrano, Yishan Zou, Stefan Slater:
Towards Generalizable Detection of Urgency of Discussion Forum Posts. - Tianze Shou, Conrad Borchers, Shamya Karumbaiah, Vincent Aleven:
Optimizing Parameters for Accurate Position Data Mining in Diverse Classrooms Layouts. - Ethan Prihar, Kirk Vanacore, Adam Sales, Neil T. Heffernan:
Effective Evaluation of Online Learning Interventions with Surrogate Measures. - Narjes Rohani, Kobi Gal, Michael Gallagher, Areti Manataki:
Early Prediction of Student Performance in a Health Data Science MOOC. - Regina Kasakowskij, Jörg M. Haake, Niels Seidel:
Self-Assessment Task Processing Behavior of Students in Higher Education. - Amruth N. Kumar:
Using Markov Matrix to Analyze Students' Strategies for Solving Parsons Puzzles. - Jean Vassoyan, Jill-Jênn Vie, Pirmin Lemberger:
Towards Scalable Adaptive Learning with Graph Neural Networks and Reinforcement Learning. - Sami Baral, Anthony Botelho, Abhishek Santhanam, Ashish Gurung, Li Cheng, Neil T. Heffernan:
Auto-scoring Student Responses with Images in Mathematics. - Tung Phung, José Cambronero, Sumit Gulwani, Tobias Kohn, Rupak Majumdar, Adish Singla, Gustavo Soares:
Generating High-Precision Feedback for Programming Syntax Errors using Large Language Models. - Mengxue Zhang, Neil T. Heffernan, Andrew S. Lan:
Modeling and Analyzing Scorer Preferences in Short-Answer Math Questions. - Yinuo Xu, Zachary A. Pardos:
Mining Detailed Course Transaction Records for Semantic Information. - Stav Tsabari, Avi Segal, Kobi Gal:
Predicting Bug Fix Time in Students' Programming with Deep Language Models.
Posters
- Gyanesh Jain, Aditya Sharma, Nirmal Patel, Amit Anil Nanavati:
Tool Usage and Efficiency in an Online Test. - Nischal Ashok Kumar, Wanyong Feng, Jaewook Lee, Hunter McNichols, Aritra Ghosh, Andrew S. Lan:
A Conceptual Model for End-to-End Causal Discovery in Knowledge Tracing. - Erwin D. López Z., Tsubasa Minematsu, Yuta Taniguchi, Fumiya Okubo, Atsushi Shimada:
LECTOR: An attention-based model to quantify e-book lecture slides and topics relationships. - Yo Ehara:
Course Concepts: How Readable Are They for ESL Learners? - Sylvio Rüdian, Clara Schumacher, Jakub Kuzilek, Niels Pinkwart:
Pre-selecting Text Snippets to provide formative Feedback in Online Learning. - Ran Bi, Shiyao Wei:
Exploring the Implementation of NLP Topic Modeling for Understanding the Dynamics of Informal Learning in an AI Painting Community. - Conrad Borchers, Lennart Klein, Hayden Johnson, Christian Fischer:
Timing Matters: Inferring Educational Twitter Community Switching from Membership Characteristics. - Luca Mouchel, Thiemo Wambsganss, Paola Mejia-Domenzain, Tanja Käser:
Understanding Revision Behavior in Adaptive Writing Support Systems for Education. - Tanya Nazaretsky, Haci Hasan Yolcu, Moriah Ariely, Giora Alexandron:
Towards Automated Assessment of Scientific Explanations in Turkish using Language Transfer. - Brad Din, Tanya Nazaretsky, Yael Feldman-Maggor, Giora Alexandron:
Automated Identification and Validation of the Optimal Number of Knowledge Profiles in Student Response Data. - Ayaz Karimov, Mirka Saarela, Tommi Kärkkäinen:
The impact of online educational platform on students' motivation and grades: the case of Khan Academy in the under-resourced communities. - Yo Ehara:
Measuring Similarity between Manual Course Concepts and ChatGPT-generated Course Concepts. - Antonette Shibani, Ratnavel Rajalakshmi, Srivarshan Selvaraj, Faerie Mattins, Dhivya Chinnappa:
Explainable models for feedback design: An argumentative writing example. - Anan Schütt, Tobias Huber, Ilhan Aslan, Elisabeth André:
Fast Dynamic Difficulty Adjustment for Intelligent Tutoring Systems with Small Datasets. - Olivier Allègre, Amel Yessad, Vanda Luengo:
Discovering prerequisite relationships between knowledge components from an interpretable learner model. - M. Parvez Rashid, Divyang Doshi, Sai Venkata Vinay, Qinjin Jia, Edward F. Gehringer:
"Can we reach agreement?": A context- and semantic-based clustering approach with semi-supervised text-feature extraction for finding disagreement in peer-assessment formative feedback. - Colton Botta, Avi Segal, Kobi Gal:
Sequencing Educational Content Using Diversity Aware Bandits. - Anirban Roy Chowdhury, Nandagopal K. S., Vijay Prakash, Syaamantak Das:
A comparative analysis of the cognitive levels of Science and Mathematics secondary school board examination questions in India. - Deliang Wang, Dapeng Shan, Yaqian Zheng, Kai Guo, Gaowei Chen, Yu Lu:
Can ChatGPT Detect Student Talk Moves in Classroom Discourse? A Preliminary Comparison with Bert.
Demonstrations
- Jinglei Yu, Zitao Liu, Mi Tian, Deliang Wang, Yu Lu:
A Multimodal Language Learning System for Chinese Character Using Foundation Model. - Arun Balajiee Lekshmi Narayanan, Khushboo Thaker, Peter Brusilovsky, Jordan Barria-Pineda:
Help Me Read! Expanding Students' Reading with Wikipedia Articles. - Haoyu Liu, Fan-Yun Sun, Frieda Rong, Kumiko Nakajima, Nicholas Haber, Shima Salehi:
Characterizing Learning Progress of Problem-Solvers Using Puzzle-Solving Log Data.
Doctoral Consortium
- Debarshi Nath, Dragan Gasevic, Ramkumar Rajendran:
A Trace-Based Generalized Multimodal SRL Framework for Reading-Writing Tasks. - K. Nisumba Soodhani:
Analyzing Team Cognition and Combined Efficacy In Makerspaces Using Multimodal Data. - Antony Prakash:
Exploring students' learning processes by logging and analyzing their interaction behavior in a Virtual Reality learning environment. - Suprabha Jadhav, Sridhar Iyer, Kavi Arya:
Data Driven Online Training Program for Education Robotics Competition. - Vishwas Badhe, Chandan Dasgupta, Ramkumar Rajendran:
Investigating teams' Socially Shared Metacognitive Regulation (SSMR) and transactivity in project-based computer supported collaborative learning environment. - Pratiksha Virendra Patil, Ashwin T. S, Ramkumar Rajendran:
Fostering Interaction in Computer-Supported Collaborative Learning Environment. - Jyoti Shaha, Ramkumar Rajendran:
Analyzing the impact of metacognition prompts on learning in CBLE. - Ram Das Rai:
Designing a Learning Environment to Foster Critical Thinking. - Guanyu Chen, Yan Liu:
Response Process Data in Educational and Psychological Assessment: A Scoping Review of Empirical Studies. - Meera Pawar, Sahana Murthy:
Understanding Learners' Alternative Conceptions through Interaction Patterns During analogical reasoning.
Tutorials
- Praveen Garimella, Vasudeva Varma:
Learning through Wikipedia and Generative AI Technologies. - Agathe Merceron, Ange Tato:
Introduction to Neural Networks and Uses in EDM. - Aaron Haim, Stacy T. Shaw, Neil T. Heffernan:
How to Open Science: Promoting Principles and Reproducibility Practices within the Educational Data Mining Community. - Ganesh Ramakrishnan, Ayush Maheshwari:
Data Efficient Machine Learning for Educational Content Creation.
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